{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Prep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T19:04:44.703941Z",
     "start_time": "2020-06-24T19:04:44.700981Z"
    }
   },
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T19:04:44.950438Z",
     "start_time": "2020-06-24T19:04:44.947013Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T19:04:45.214364Z",
     "start_time": "2020-06-24T19:04:45.212142Z"
    }
   },
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')\n",
    "idx = pd.IndexSlice\n",
    "deciles = np.arange(.1, 1, .1).round(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T19:04:46.327976Z",
     "start_time": "2020-06-24T19:04:46.325809Z"
    }
   },
   "outputs": [],
   "source": [
    "DATA_STORE = Path('..', 'data', 'assets.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T19:04:50.981867Z",
     "start_time": "2020-06-24T19:04:46.486585Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    data = (store['quandl/wiki/prices']\n",
    "            .loc[idx['2007':'2016', :],\n",
    "                 ['adj_open', 'adj_high', 'adj_low', 'adj_close', 'adj_volume']]\n",
    "            .dropna()\n",
    "            .swaplevel()\n",
    "            .sort_index()\n",
    "            .rename(columns=lambda x: x.replace('adj_', '')))\n",
    "    metadata = store['us_equities/stocks'].loc[:, ['marketcap', 'sector']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T19:04:51.136864Z",
     "start_time": "2020-06-24T19:04:50.982865Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "MultiIndex: 6951874 entries, ('A', Timestamp('2007-01-03 00:00:00')) to ('ZUMZ', Timestamp('2016-12-30 00:00:00'))\n",
      "Data columns (total 5 columns):\n",
      " #   Column  Non-Null Count    Dtype  \n",
      "---  ------  --------------    -----  \n",
      " 0   open    6951874 non-null  float64\n",
      " 1   high    6951874 non-null  float64\n",
      " 2   low     6951874 non-null  float64\n",
      " 3   close   6951874 non-null  float64\n",
      " 4   volume  6951874 non-null  float64\n",
      "dtypes: float64(5)\n",
      "memory usage: 291.8+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info(null_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T19:04:51.143923Z",
     "start_time": "2020-06-24T19:04:51.138132Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 6834 entries, PIH to ZYME\n",
      "Data columns (total 2 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   marketcap  5766 non-null   float64\n",
      " 1   sector     6834 non-null   int64  \n",
      "dtypes: float64(1), int64(1)\n",
      "memory usage: 160.2+ KB\n"
     ]
    }
   ],
   "source": [
    "metadata.sector = pd.factorize(metadata.sector)[0]\n",
    "metadata.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T19:04:51.574464Z",
     "start_time": "2020-06-24T19:04:51.145226Z"
    }
   },
   "outputs": [],
   "source": [
    "data = data.join(metadata).dropna(subset=['sector'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T19:04:51.707088Z",
     "start_time": "2020-06-24T19:04:51.575429Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "MultiIndex: 5395695 entries, ('A', Timestamp('2007-01-03 00:00:00')) to ('ZUMZ', Timestamp('2016-12-30 00:00:00'))\n",
      "Data columns (total 7 columns):\n",
      " #   Column     Non-Null Count    Dtype  \n",
      "---  ------     --------------    -----  \n",
      " 0   open       5395695 non-null  float64\n",
      " 1   high       5395695 non-null  float64\n",
      " 2   low        5395695 non-null  float64\n",
      " 3   close      5395695 non-null  float64\n",
      " 4   volume     5395695 non-null  float64\n",
      " 5   marketcap  5385154 non-null  float64\n",
      " 6   sector     5395695 non-null  float64\n",
      "dtypes: float64(7)\n",
      "memory usage: 308.9+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info(null_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T19:04:51.762455Z",
     "start_time": "2020-06-24T19:04:51.708070Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Tickers: 2,399 | # Dates: 2,547\n"
     ]
    }
   ],
   "source": [
    "print(f\"# Tickers: {len(data.index.unique('ticker')):,.0f} | # Dates: {len(data.index.unique('date')):,.0f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Select 500 most-traded stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:45.959128Z",
     "start_time": "2020-06-24T15:47:45.947288Z"
    }
   },
   "outputs": [],
   "source": [
    "dv = data.close.mul(data.volume)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:48.895686Z",
     "start_time": "2020-06-24T15:47:45.960057Z"
    }
   },
   "outputs": [],
   "source": [
    "top500 = (dv.groupby(level='date')\n",
    "          .rank(ascending=False)\n",
    "          .unstack('ticker')\n",
    "          .dropna(thresh=8*252, axis=1)\n",
    "          .mean()\n",
    "          .nsmallest(500))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize the 200 most liquid stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:52.893866Z",
     "start_time": "2020-06-24T15:47:48.896584Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top200 = (data.close\n",
    "          .mul(data.volume)\n",
    "          .unstack('ticker')\n",
    "          .dropna(thresh=8*252, axis=1)\n",
    "          .mean()\n",
    "          .div(1e6)\n",
    "          .nlargest(200))\n",
    "cutoffs = [0, 50, 100, 150, 200]\n",
    "fig, axes = plt.subplots(ncols=4, figsize=(20, 10), sharex=True)\n",
    "axes = axes.flatten()\n",
    "\n",
    "for i, cutoff in enumerate(cutoffs[1:], 1):\n",
    "    top200.iloc[cutoffs[i-1]:cutoffs[i]\n",
    "                ].sort_values().plot.barh(logx=True, ax=axes[i-1])\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:52.928720Z",
     "start_time": "2020-06-24T15:47:52.896349Z"
    }
   },
   "outputs": [],
   "source": [
    "to_drop = data.index.unique('ticker').difference(top500.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:52.932940Z",
     "start_time": "2020-06-24T15:47:52.929800Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1899"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(to_drop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:57.918766Z",
     "start_time": "2020-06-24T15:47:52.934280Z"
    }
   },
   "outputs": [],
   "source": [
    "data = data.drop(to_drop, level='ticker')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:57.959127Z",
     "start_time": "2020-06-24T15:47:57.919984Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "MultiIndex: 1256095 entries, ('A', Timestamp('2007-01-03 00:00:00')) to ('ZION', Timestamp('2016-12-30 00:00:00'))\n",
      "Data columns (total 7 columns):\n",
      " #   Column     Non-Null Count    Dtype  \n",
      "---  ------     --------------    -----  \n",
      " 0   open       1256095 non-null  float64\n",
      " 1   high       1256095 non-null  float64\n",
      " 2   low        1256095 non-null  float64\n",
      " 3   close      1256095 non-null  float64\n",
      " 4   volume     1256095 non-null  float64\n",
      " 5   marketcap  1253855 non-null  float64\n",
      " 6   sector     1256095 non-null  float64\n",
      "dtypes: float64(7)\n",
      "memory usage: 72.0+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info(null_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:57.974742Z",
     "start_time": "2020-06-24T15:47:57.960002Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Tickers: 500 | # Dates: 2,518\n"
     ]
    }
   ],
   "source": [
    "print(f\"# Tickers: {len(data.index.unique('ticker')):,.0f} | # Dates: {len(data.index.unique('date')):,.0f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Remove outlier observations based on daily returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:58.161674Z",
     "start_time": "2020-06-24T15:47:57.976841Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dropped 502\n"
     ]
    }
   ],
   "source": [
    "before = len(data)\n",
    "data['ret'] = data.groupby('ticker').close.pct_change()\n",
    "data = data[data.ret.between(-1, 1)].drop('ret', axis=1)\n",
    "print(f'Dropped {before-len(data):,.0f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:58.180734Z",
     "start_time": "2020-06-24T15:47:58.162744Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Tickers: 500 | # Dates: 2,517\n"
     ]
    }
   ],
   "source": [
    "tickers = data.index.unique('ticker')\n",
    "print(f\"# Tickers: {len(tickers):,.0f} | # Dates: {len(data.index.unique('date')):,.0f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sample price data for illustration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:58.197385Z",
     "start_time": "2020-06-24T15:47:58.182931Z"
    }
   },
   "outputs": [],
   "source": [
    "ticker = 'AAPL'\n",
    "# alternative\n",
    "# ticker = np.random.choice(tickers)\n",
    "price_sample = data.loc[idx[ticker, :], :].reset_index('ticker', drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:58.204678Z",
     "start_time": "2020-06-24T15:47:58.198444Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 2517 entries, 2007-01-04 to 2016-12-30\n",
      "Data columns (total 7 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   open       2517 non-null   float64\n",
      " 1   high       2517 non-null   float64\n",
      " 2   low        2517 non-null   float64\n",
      " 3   close      2517 non-null   float64\n",
      " 4   volume     2517 non-null   float64\n",
      " 5   marketcap  2517 non-null   float64\n",
      " 6   sector     2517 non-null   float64\n",
      "dtypes: float64(7)\n",
      "memory usage: 157.3 KB\n"
     ]
    }
   ],
   "source": [
    "price_sample.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:58.214107Z",
     "start_time": "2020-06-24T15:47:58.205896Z"
    }
   },
   "outputs": [],
   "source": [
    "price_sample.to_hdf('data.h5', 'data/sample')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute returns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Group data by ticker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:58.243147Z",
     "start_time": "2020-06-24T15:47:58.215061Z"
    }
   },
   "outputs": [],
   "source": [
    "by_ticker = data.groupby(level='ticker')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Historical returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:58.247605Z",
     "start_time": "2020-06-24T15:47:58.244576Z"
    }
   },
   "outputs": [],
   "source": [
    "T = [1, 2, 3, 4, 5, 10, 21, 42, 63, 126, 252]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:58.714067Z",
     "start_time": "2020-06-24T15:47:58.248645Z"
    }
   },
   "outputs": [],
   "source": [
    "for t in T:\n",
    "    data[f'ret_{t:02}'] = by_ticker.close.pct_change(t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Forward returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:58.858563Z",
     "start_time": "2020-06-24T15:47:58.714973Z"
    }
   },
   "outputs": [],
   "source": [
    "data['ret_fwd'] = by_ticker.ret_01.shift(-1)\n",
    "data = data.dropna(subset=['ret_fwd'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Persist results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:58.917072Z",
     "start_time": "2020-06-24T15:47:58.859512Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "MultiIndex: 1255093 entries, ('A', Timestamp('2007-01-04 00:00:00')) to ('ZION', Timestamp('2016-12-29 00:00:00'))\n",
      "Data columns (total 19 columns):\n",
      " #   Column     Non-Null Count    Dtype  \n",
      "---  ------     --------------    -----  \n",
      " 0   open       1255093 non-null  float64\n",
      " 1   high       1255093 non-null  float64\n",
      " 2   low        1255093 non-null  float64\n",
      " 3   close      1255093 non-null  float64\n",
      " 4   volume     1255093 non-null  float64\n",
      " 5   marketcap  1252855 non-null  float64\n",
      " 6   sector     1255093 non-null  float64\n",
      " 7   ret_01     1254593 non-null  float64\n",
      " 8   ret_02     1254093 non-null  float64\n",
      " 9   ret_03     1253593 non-null  float64\n",
      " 10  ret_04     1253093 non-null  float64\n",
      " 11  ret_05     1252593 non-null  float64\n",
      " 12  ret_10     1250093 non-null  float64\n",
      " 13  ret_21     1244593 non-null  float64\n",
      " 14  ret_42     1234093 non-null  float64\n",
      " 15  ret_63     1223593 non-null  float64\n",
      " 16  ret_126    1192093 non-null  float64\n",
      " 17  ret_252    1129093 non-null  float64\n",
      " 18  ret_fwd    1255093 non-null  float64\n",
      "dtypes: float64(19)\n",
      "memory usage: 186.9+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info(null_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-24T15:47:59.077916Z",
     "start_time": "2020-06-24T15:47:58.918343Z"
    }
   },
   "outputs": [],
   "source": [
    "data.to_hdf('data.h5', 'data/top500')"
   ]
  }
 ],
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